Adaptive random neighborhood community division algorithm based on modularity optimization

A technology for dividing algorithms and modularity, applied in computing, data processing applications, forecasting, etc., can solve problems such as lack of attention to the stability of algorithm results, and achieve the effect of improving computing speed, reducing the number of times, and ensuring accuracy and stability.

Inactive Publication Date: 2018-08-10
FUDAN UNIV
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Problems solved by technology

[0008] At present, domestic and foreign scholars' research on community division algorithms mainly focuses on the proposal of heuristic algorithms and the improvement of algorithm running speed, but pays little attention to the stability of algorithm results.

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  • Adaptive random neighborhood community division algorithm based on modularity optimization
  • Adaptive random neighborhood community division algorithm based on modularity optimization
  • Adaptive random neighborhood community division algorithm based on modularity optimization

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Embodiment Construction

[0039] In order to make the technical problems to be solved by the present invention, technical solutions and advantages of the invention clearer, the present invention will be described in detail below in conjunction with the accompanying drawings and embodiments. It should be noted that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0040] The invention is a novel community division algorithm for network analysis—adaptive random neighbor algorithm based on modularity optimization (abbreviated as RSNL). As an example, this application will use a karate club network to demonstrate the division process of this algorithm. The karate club network contains 34 nodes and 78 edges. This network is a classic network used for community division.

[0041] First, if figure 1 As shown, after inputting the karate club network data set into this algorithm, initially, all nodes are in an independent comm...

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Abstract

The invention discloses an adaptive random neighborhood community division algorithm based on modularity optimization. By use of the algorithm, through a way of randomly extracting parts of neighborhood nodes to calculate a modularity gain, the nodes are moved to a community which can bring the maximum modularity gain so as to carry out community division on the network. The algorithm has the characteristics of being accurate, stable, high in operation speed and adaptive. The algorithm, a classic Louvain algorithm and a random neighborhood Louvain algorithm are verified in an LFR artificial reference map network and a plurality of demonstration networks, indexes, including the modularity, single-time operation time, mutation coefficients, equivalent operation time and the like, are used for evaluation, and a result highlights the adaptive characteristics of the algorithm and higher practical application efficiency.

Description

technical field [0001] The invention belongs to the technical field of community division algorithms in complex networks, and in particular relates to an adaptive random neighbor community division algorithm based on modularity optimization that uses the principle of small probability events to select neighbor nodes on the basis of Louvain's classic algorithm principle. Background technique [0002] The study of complex networks has received more and more attention from scholars in recent years. With the gradual deepening of research on complex networks, it is found that there is a unique structural feature in the network, which is called community structure. Studies have found that community structure is usually closely related to the dynamic behavior and functional characteristics of the network. Analyzing the community structure of the network is an important step in the study of complex networks. [0003] Users in the same community are closely connected, and users in ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/00
CPCG06Q10/04G06Q50/01
Inventor 张子乔韩定定蒲鹏唐明
Owner FUDAN UNIV
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